ABSTRACT:
As digital platform ecosystems grow in prominence, their interconnectedness and complexity also grow, making operational failure likely. How failures in such systems affect user perceptions of separate ecosystem components, however, is not well understood. This research investigates attribution of responsibility and discontinuance recommend ations for ecosystem components after failures of ambiguous origin. Building on attribution theory, platform ecosystems literature, and research on digital borders, we conducted two scenario-based experiments investigating negative consequences of failure for ecosystem components. We also explored contingent effects from design elements (border strength) and contextual factors (disruption severity). Results demonstrated that when failures occur, negative consequences diffuse to all ecosystem components, with apps receiving the strongest discontinuance recommendations. Greater disruption severity increased discontinuance recommendations for the app. Furthermore, border strength between ecosystem components shifted negative consequences for failure toward the platform (e.g., operating system [OS] and device). Perceptions of locus and controllability were the primary mechanisms driving attributions of responsibility for failure. However, contrary to attribution theory, lack of failure stability increased blame for the app instead of reducing it. Despite higher coordination costs, our results indicate the importance of better-integrated ecosystems that experience fewer faults and that app developers bear the greatest burden in delivering this experience. Furthermore, attribution for failure can be shaped by clearly delineated borders. Thus, design decisions affecting border strength should be actively managed by ecosystem participants, and app developers may be incentivized to elevate border strength.
Key words and phrases: Mobile platforms, digital platforms, mobile platform ecosystems, system failure, ambiguous failure, blame attribution, system discontinuance, failure attribution